A Modified Active Anti-Disturbance Control for a Nonlinear CSTR Model

Active Anti-Disturbance Control, which so far had reportedly been applied to linear plant models, has been extended in this work to cover control of nonlinear plant models. To accommodate nonlinear plants, an Internal Model Controller (IMC) and a Disturbance Observer (DOB) for nonlinear systems have been used innovatively in the design architecture. It is conjectured that the IMC approach would mitigate plant parameter perturbations whereas the DOB would take care of external disturbances together to conjugatively produce a more robust closed loop plant. To illustrate the proposed algorithm, viz., Modified Active Anti-Disturbance Control (MAADC), the proposed technique has been employed to control a nonlinear Continuous Stirred Tank Reactor (CSTR) system. It is shown that strong external disturbances and model uncertainties have been actively mitigated by using the proposed MAADC, indicating superior robustness compared to ordinary nonlinear IMC based control. Different set-point and disturbance conditions have been considered to characterize the algorithm.

A Fault Tolerant Vehicle Stability Control Using Adaptive Control Allocation

This paper presents an integrated fault-tolerant adaptive control allocation strategy for four wheel frive - four wheel steering ground vehicles to increase yaw stability. Conventionally, control of brakes, motors and steering angles are handled separately. In this study, these actuators are controlled simultaneously using an adaptive control allocation strategy. The overall structure consists of two steps: At the first level, virtual control input consisting of the desired traction force, the desired moment correction and the required lateral force correction to maintain driver’s intention are calculated based on the driver’s steering and throttle input and vehicle’s side slip angle. Then, the allocation module determines the traction forces at each wheel, front steering angle correction and rear steering wheel angle, based on the virtual control input. Proposed strategy is validated using a non-linear three degree of freedom reduced two-track vehicle model and results demonstrate that the vehicle can successfully follow the reference motion while protecting yaw stability, even in the cases of device failure and changed road conditions.

Predictively Coordinated Vehicle Acceleration and Lane Selection Using Mixed Integer Programming

Autonomous vehicle technology provides the means to optimize motion planning beyond human capacity. In particular, the problem of navigating multi-lane traffic optimally for trip time, energy efficiency, and collision avoidance presents challenges beyond those of single-lane roadways. For example, the host vehicle must simultaneously track multiple obstacles, the drivable region is non-convex, and automated vehicles must obey social expectations. Furthermore, reactive decision-making may result in becoming stuck in an undesirable traffic position. This paper presents a fundamental approach to these problems using model predictive control with a mixed integer quadratic program at its core. Lateral and longitudinal movements are coordinated to avoid collisions, track a velocity and lane, and minimize acceleration. Vehicle-to-vehicle connectivity provides a preview of surrounding vehicles’ motion. Simulation results show a 79% reduction in congestion-induced travel time and an 80% decrease in congestion-induced fuel consumption compared to a rule-based approach.

Stiffness Control of Parallel Continuum Robots

Parallel continuum robots can provide compact, compliant manipulation of tools in robotic surgery and larger-scale human robot interaction. In this paper we address stiffness control of parallel continuum robots using a general nonlinear kinetostatic modeling framework based on Cosserat rods. We use a model formulation that estimates the applied end-effector force and pose using actuator force measurements. An integral control approach then modifies the commanded target position based on the desired stiffness behavior and the estimated force and position. We then use low-level position control of the actuators to achieve the modified target position. Experimental results show that after calibration of a single model parameter, the proposed approach achieves accurate stiffness control in various directions and poses.

Variability in Muscle Recruitment Strategy Between Operators During Assisted Assembly Tasks

This paper reports the variability in muscle recruitment strategies among individuals who operate a non-powered lifting device for general assembly (GA) tasks. Support vector machine (SVM) was applied to the classification of motion states of operators using electromyography (EMG) signals collected from a total of 15 upper limb, lower limb, shoulder, and torso muscles. By comparing the classification performance and muscle activity features, variability in muscle recruitment strategy was observed from lower limb and torso muscles, while the recruitment strategies of upper limb and shoulder muscles were relatively consistent across subjects. Principal component analysis (PCA) was applied to identify key muscles that are highly correlated with body movements. Selected muscles at the wrist joint, ankle joint and scapula are considered to have greater significance in characterizing the muscle recruitment strategies than other investigated muscles. PCA loading factors also indicate the existence of body motion redundancy during typical pick-and-place tasks.

Identification of Compensatory Arterial Dynamics in Swine Using a Non-Invasive Sensor for Local Vascular Resistance

Autoregulatory dynamics of the cardiovascular system play an important role in maintaining oxygenated blood transportation throughout the human body. In this work, a feedback dynamics model of the cardiovascular system with respect to heartrate and peripheral vascular resistance effects on longer-term blood pressure changes in the systemic circulation is presented. The model is identified from data taken from a swine test subject, instrumented in part with a wearable, non-invasive sensor for estimating peripheral arterial radius. Comparative simulations for the open and close loop model highlight significantly changed hemodynamics after hemorrhage.

Design Optimization of RML Glove for Improved Grasp Performance

This paper describes the design optimization of the RML Glove in order to improve its grasp performance. The existing design is limited to grasping objects of large diameter (> 110mm) due to its inability in attaining high bending angles. For an exoskeleton glove to be effective in its use as an assistive and rehabilitation device for Activities of Daily Living (ADL), it should be able to interact with objects over a wide range of sizes. Motivated by these limitations, the kinematics of the existing linkage mechanism was analyzed in detail and the design variables were identified. Two different cost functions were formulated and compared in their ability to yield optimal values for the design variables. The optimal set of design variables was chosen based on the grasp angles achieved and the resulting mechanism was simulated in CAD for feasibility testing. An exoskeleton mechanism corresponding to the index finger was manufactured with the chosen design variables and detailed experimental validation was performed to illustrate the improvement in grasp performance over the existing design. The paper ends with a summary of the experimental results and directions for future research.

Capturability of Inverted Pendulum Gait Model Under Slip Conditions

This paper presents a simple inverted pendulum gait model to study walking under slip conditions. The model allows for both the horizontal and vertical movements of the center of mass during normal walking and walking gaits with foot slip. Stability of the system is analyzed using the concept of capturability. Considering foot placement as a control input, we obtain the stable regions which lead to stable gait. The size of those stable regions is used to evaluate the effect of the coefficient of friction and the slip reaction time on capturability. We also analyze the feasibility of recovery from slip gait in relation to the coefficient of friction and the reaction time. The results confirm the effectiveness of the model and the capturability developement.

A Robotic Ankle-Foot Orthosis for Daily-Life Assistance and Rehabilitation

The ankle plays an important role in human movement as it supplies the majority of energy to support an individual’s walking. In this paper, the authors present a robotic ankle-foot orthosis (RAFO), which is essentially a wearable robot that acts in parallel to the user’s biological ankle for motion assistance. Unlike most of the existing robotic ankle-foot ortheses, the RAFO in this paper is a compact and portable assistive device with full energy autonomy, which enables its use in a user’s daily life without the typical limitation associated with tethered operation. The primary performance goal in the design of the RAFO is to provide a torque capacity equivalent to 35% of a 75 kg healthy person’s maximum ankle torque in slow walking, while keeping the weight of the device less than 2 kg. To reach such goal, the orthotic joint is actuated with a compact flat motor coupled with a two-stage transmission that provides a total 200:1 gear ratio. Additionally, a novel two-degree-of-freedom (2-DOF) joint design is incorporated. In addition to the powered dorsiflexion – plantarflexion, the 2-DOF joint also allows passive inversion – eversion of the joint, which greatly improves the comfort in the prolonged wearing of the device. For the control of the powered joint, a finite-state, friction-compensated impedance controller is developed to provide natural interaction with the user and reliable triggering of the powered push-off in walking. A prototype of the RAFO has been fabricated and assembled, and preliminary results demonstrated its effectiveness in assisting the user’s locomotion in treadmill walking experiments.

Analytical and Experimental Predictor-Based Time Delay Control of Baxter Robot

In this paper, a predictor-based controller for a 7-DOF Baxter manipulator is formulated to compensate a time-invariant input delay during a pick-and-place task. Robot manipulators are extensively employed because of their reliable, fast, and precise motions although they are subject to large time delays like many engineering systems. The time delay may lead to the lack of high precision required and even catastrophic instability. Using common control approaches on such delay systems can cause poor control performance, and uncompensated input delays can produce hazards when used in engineering applications. Therefore, destabilizing time delays need to be regarded in designing control law. First, delay-free dynamic equations are derived using the Lagrangian method. Then, we formulate a predictor-based controller for a 7-DOF Baxter manipulator, in the presence of input delay, in order to track desirable trajectories. Finally, the results are experimentally evaluated.